I'm a third-year engineering student at LNMIIT (CGPA: 8.16) obsessed with data science, machine learning, and generative AI. I don't just learn from textbooks—I build. Every project is an experiment, every problem set is a real-world challenge. My philosophy: consistency beats intensity, and impact matters more than perfection.
Currently hunting for Data Science / ML internships and entry-level roles at growth-stage companies and startups. I thrive in remote-first environments, love asynchronous collaboration, and I'm always ready to solve hard problems for ambitious teams.
- 🏢 Data Science / ML Internships & Fresher Roles
- 🌍 Remote opportunities with global startups (Europe-friendly time zones welcome)
- 💼 Freelance problem-solving & contract ML work
- 🚀 Early-stage startup founding teams
- 🔬 Research collaborations in GenAI & RAG systems
| Languages | ML/AI | Tools & Deployment |
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Specialized Skills:
- 🧠 NLP & Transformers (BERT, GPT, RAG systems)
- 🤖 Generative AI (Prompt Engineering, Fine-tuning, API Integration)
- 📊 Data Pipelines (ETL, preprocessing, feature engineering)
- 🎯 Forecasting & Time Series (LSTM, XGBoost, demand prediction)
- 🔗 System Architecture (Microservices, APIs, CI/CD)
✅ Ownership-driven — I own projects end-to-end, from conception to deployment
✅ Consistency over heroics — I show up daily and compound small wins
✅ Learning in public — I document my journey and share insights openly
✅ Impact-first thinking — Every line of code solves a real problem
✅ Practical problem solver — Theory is useful, but results matter
- Designed intelligent chatbot using BERT (intent classification) + GPT (response generation)
- Built ETL pipelines for historical data → achieved 80% classification accuracy
- FastAPI backend for real-time responses with human handoff capability
- Hackathon Finalist at NIT Delhi
- Automated competitor monitoring via web scraping + daily updates
- XGBoost model predicting demand with 82% accuracy
- Deployed via Docker + CI/CD → 60% faster deployments
- Streamlit frontend for interactive insights
- LSTM-based forecasting for next-day + next-minute predictions
- Automated ETL pipelines with dynamic retraining per ticker
- Flask API deployed on Render for live market data ingestion
- GenAI + RAG integration for question generation, summaries, voice assistance
- Tested with 50+ academic queries → 80% response relevance
- Voice-enabled interface with Google OAuth authentication
- Team Leader | Selected for technical innovation
| Area | What I'm Doing |
|---|---|
| ML Ops & Automation | Building scalable pipelines, experimenting with fine-tuning workflows |
| GenAI Exploration | Prompt engineering, RAG optimization, integrating cutting-edge APIs |
| Problem Solving | Daily DSA practice, SQL optimization challenges, system design thinking |
| Portfolio Building | Publishing polished projects with documentation, blogging insights |
| Networking | Contributing to open-source, engaging with ML communities, connecting with founders |
🎯 I'm actively accepting:
- Data Science / ML internships (immediate start)
- Contract ML engineering work
- Freelance data analysis & modeling projects
- Conversations with founders building AI-first products
- Research collaborations in NLP & generative AI
Let's talk if you're building something ambitious and need someone who:
- Thinks in systems and outcomes, not just code
- Moves fast without cutting corners
- Actually ships things
Last Updated: January 2026 | Always learning, always building 🚀